Susmita Dasgupta
Lead Environmental Economist, Development Research Group, World Bank
Md. Moqbul Hossain
Principal Scientific Officer, Soil Research Development Institute, Ministry of Agriculture, Bangladesh
Mainul Huq
Consultant, World Bank
David Wheeler
Senior Fellow, World Resources Institute
Climate Change, Coastal Areas, Soil Salinity, Agriculture, Rice Production
Socio-economic and Policy
Climate change, Rice
3. Study Area It comprises 140 upazilas in four regions of southern Bangladesh: Barisal (38 upazilas), Chittagong (30), Dhaka (13) and Khulna (59). Identifies these upazilas by region, district and sub-district, as well as summarizing available information on HYV rice yields. The study area spans the southern coastal regions of Bangladesh, with extensions to permit assessment of current and future salinity further inland. Study teams have collected available data on agricultural production for the period 2000-2012 from local offices in each upazila. In many cases, we believe that these data have not previously been available for empirical research.
4.2 Soil Salinity While the Dasgupta study provides a trove of new evidence on salinity change in Bangladesh’s coastal rivers, no comparable assessment of soil salinity has been undertaken until now. For this study, the Bangladesh Soil Research Development Institute has provided measures from 41 soil salinity monitoring stations for the period 2001-2009. Average monthly station measures for 2001-2009, color-coded in five groups for visual comparison with the distribution of readings from the river stations. The distribution of soil salinity measures bears some resemblance to the riverine distribution, particularly in the concentration of high salinity in central Khulna. However, It reveals some marked differences as well. For example, the soil salinity measures in Barisal are relatively higher than their riverine counterparts.
4.3 Determinants of Soil Salinity As we noted in the Introduction, one major objective of this study is an econometrically estimated model that can be used to project soil salinity for HYV rice production areas in the coastal region of Bangladesh through 2050. In our model, land-based measures of soil salinity are related to salinity measures from nearby river stations via annual flooding and water table infusion. Logically, infusion effects and salinity should decline with elevation. In addition, dilution from precipitation should produce a negative relationship between soil salinity and rainfall. Finally, measured soil salinity rises with temperature because our soil salinity measure is based on electrical conductivity, which is greater at higher temperatures.
4.4 Data Our data set includes monthly soil salinity measures from 41 stations for the period 2001-2009, provided by the Bangladesh Soil Research Development Institute; water salinity measures from 29 stations for 2000-2008, provided by Dasgupta et al. (2014); elevation data from DIVA-GIS;6 and monthly temperature and rainfall data from 20 BMD weather stations for 1990-2010.7 As Figures 3, 4 and 5 show, the monitoring stations for soil salinity, river salinity and weather are located in different places, at varying distances from one another. Estimation of equation (1) requires juxtaposition of soil salinity, river salinity, temperature and rainfall at soil monitoring locations. For river salinity, we incorporate measures for all river stations within 30 km of each soil salinity monitor. We capture relative diffusion impacts using weights for river stations that are inversely proportional to their squared distances from the soil stations. For weather stations, we use observations for the station that is closest to each soil salinity monitor.
Policy Research Working Paper 7140 Development Research Group December 2014
Journal